DS 4320 Project 1: Building a Relational Movie Recommendation Dataset from MovieLens

This project builds a relational secondary dataset from the MovieLens “latest small” dataset to support personalized movie recommendations. The raw data is transformed into a normalized relational structure with linked tables for users, movies, ratings, tags, links, genres, and movie_genres. Using Python, SQL, DuckDB, and collaborative filtering, the project demonstrates how relational data design and machine learning can be used together to recommend movies a user is likely to enjoy.